# mbetaTopN

Syntax

mbetaTopN(X, Y, S, window, top, [ascending=true])

Please see Moving TopN Functions (mTopN functions) for the parameters and windowing logic.

Details

After stably sorting S in the specified ascending order, the function obtains the first top pairs of elements in X and Y in the sliding window and calculate the coefficient estimate ordinary-least-squares regressions of Y on X.

Examples

```\$ x = NULL 3 8 4 0
\$ y = 2 3 1 7 3
\$ s = 5 NULL 8 9 4
\$ mbetaTopN(x, y, s, 3, 2)
[ , , , -2.5, -4]

\$ s2=2021.01.01 2021.02.03 2021.01.23 2021.04.06 2021.12.29
\$ mbetaTopN(x, y, s2, 3, 2)
[ , , , -2.5, -0.6667]

\$ x1 = matrix(x, 4 3 6 2 3)
\$ y1=matrix(3 7 9 3 2, y)
\$ s1=matrix(2 3 1 7 3, s)

\$ mbetaTopN(x, y1, s1, 3, 2)
```

col1

col2

2.5

-2.5

1.1429

-4

```\$ mbetaTopN(x1, y1, s, 3, 2)
```

col1

col2

-1

-1

2.5

-1.5

1.1429

-1.5

```\$ mbetaTopN(x1, y1, s, 3, 2)
```

col1

col2

-1

-1

2.5

-1.5

1.1429

-1.5

```\$ n = 3000
\$ ids = 1..3000
\$ dates = take(2021.01.01..2021.10.01,n)
\$ prices = rand(1000,n)
\$ vals = rand(1000,n)
\$ t = table(ids as id,dates as date,prices as price,vals as val)
\$ dbName = "dfs://test_mbetaTopN_2"
\$ if(existsDatabase(dbName))dropDB(dbName)
\$ db = database(dbName,VALUE,1..5000)
\$ pt = db.createPartitionedTable(t,"pt",`id).append!(t)
\$ select mbetaTopN(price, val, id, 10, 5, true) from pt where date>2021.05.01
```

Related function: mbeta